Ontology-based information extraction is considered as an effective method to improve the performance of information extraction (IE) systems. For research and disbursal of customized healthcare services, a major challenge is to efficiently retrieve and analyse the individual patient data from a large volume of heterogeneous data over a long span of time. This requires effective ontology-based information retrieval approaches for clinical information systems. This book is an attempt to highlight the key advances in ontology-based information retrieval techniques especially in the healthcare domain. The varied chapters attempt to uncover the current challenges in the application of ontology-based information retrieval techniques to the healthcare systems. This book is the first of its kind that highlights the ontology-driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems. It can serve as a textbook for courses in healthcare systems. It can also serve as a reference book to medical practitioners and researchers involved in implementing as well as providing customised health care solutions to patients.
Preface; Ontology-Based Information Retrieval System Using Blockchain for Reducing Cost of Customized Healthcare System; Ontological Multi-Agent System for Pandemic Zone Classification and Automated Policy Formation; An Overview of Ontology-Based Artificial Intelligence Services in Health Care Systems; DLCDI: A Novel Deep Learning Mechanism for Chronic Diseases Identification; Novel Approach to Health Monitoring System; IoT in Healthcare Applications, Benefits, Challenges, Real-Time Uses, and Cases; Data Privacy and Security in Healthcare; Examining the Effect of Ashes of Vedic Homa and Its Scientific Impacts on AQI with Social Perspectives: An ML and CPS Based Experimental Study for Delhi-NCR Zone amidst Pandemic Threats; NLP: Smart Texting System Based on Android; Storing and Maintaining the Smart Healthcare in IoT Environment; Index.
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